The constraints to learning in birdsong

In this work we explore the constraints that the structure of the neural motor program imposes to the possible songs learned by oscine birds. We carry out this program by translating anatomical information on the structure of these nuclei into a computational model. We investigate with analytical an...

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Autores principales: Trevisan, M.A., Mindlin, G.B.
Formato: JOUR
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19516355_v146_n1_p199_Trevisan
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
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spelling todo:paper_19516355_v146_n1_p199_Trevisan2023-10-03T16:37:22Z The constraints to learning in birdsong Trevisan, M.A. Mindlin, G.B. In this work we explore the constraints that the structure of the neural motor program imposes to the possible songs learned by oscine birds. We carry out this program by translating anatomical information on the structure of these nuclei into a computational model. We investigate with analytical and numeral tools this model, and use its solutions to generate synthetic songs. This allows us to perform specific predictions on the simultaneous measurement of acoustic features and the physiological variables during the song. © EDP Sciences/ Societé Italiana di Fisica/Springer-Verlag 2007. Fil:Trevisan, M.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_19516355_v146_n1_p199_Trevisan
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
description In this work we explore the constraints that the structure of the neural motor program imposes to the possible songs learned by oscine birds. We carry out this program by translating anatomical information on the structure of these nuclei into a computational model. We investigate with analytical and numeral tools this model, and use its solutions to generate synthetic songs. This allows us to perform specific predictions on the simultaneous measurement of acoustic features and the physiological variables during the song. © EDP Sciences/ Societé Italiana di Fisica/Springer-Verlag 2007.
format JOUR
author Trevisan, M.A.
Mindlin, G.B.
spellingShingle Trevisan, M.A.
Mindlin, G.B.
The constraints to learning in birdsong
author_facet Trevisan, M.A.
Mindlin, G.B.
author_sort Trevisan, M.A.
title The constraints to learning in birdsong
title_short The constraints to learning in birdsong
title_full The constraints to learning in birdsong
title_fullStr The constraints to learning in birdsong
title_full_unstemmed The constraints to learning in birdsong
title_sort constraints to learning in birdsong
url http://hdl.handle.net/20.500.12110/paper_19516355_v146_n1_p199_Trevisan
work_keys_str_mv AT trevisanma theconstraintstolearninginbirdsong
AT mindlingb theconstraintstolearninginbirdsong
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AT mindlingb constraintstolearninginbirdsong
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